• Journal of Navigation and Port Research
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• v.47 no.6
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• pp.437-447
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• 2023

By actively adopting technologies from the Fourth Industrial Revolution, the port industry is trending toward new types of ports, such as automated and smart ports. However, behind the development of these ports, there is an increasing risk of cyber security incidents and threats within ports and container terminals, including information leakage through cargo handling equipment and ransomware attacks leading to disruptions in terminal operations. Despite the necessity of research to enhance cyber security within ports, there is a lack of such studies in the domestic context. This study focuses on Busan Port, a representative port in South Korea that actively incorporates technology from the Fourth Industrial Revolution, in order to discover variables for improving cyber security in container terminals. The research results categorized factors for enhancing cyber security in Busan Port's container terminals into network construction and policy support, standardization of education and personnel training, and legal and regulatory factors. Subsequently, multiple regression analysis was conducted based on these factors, leading to the identification of detailed factors for securing and enhancing safety, reliability, performance, and satisfaction in Busan Port's container terminals. The significance of this study lies in providing direction for enhancing cyber security in Busan Port's container terminals and addressing the increasing incidents of cyber security attacks within ports and container terminals.

• Journal of the Korean Applied Science and Technology
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• v.40 no.4
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• pp.773-785
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• 2023

This study is a descriptive research conducted to identify the factors influencing patient safety management activities of geriatric hospitals nurses and use basic data to prevent patient safety accidents. Subjects were 220 nurses and data were collected by questionnaires from february 1 to 28, 2023. Data were analyzed using t-test, ANOVA, Scheffe's test, Pearson correlation coefficients and Multiple regression analysis using the SPSS 29.0 program. Patient safety motivation was positive correlated with degree of patient safety(r=.41, p<.001), and degree of patient safety was positive correlated with patient safety nursing activity(r=.18, p<.01). Degree of patient safety(𝛽=.21, p<.001) and patient safety guidelines(𝛽=.16, p<.001) were main factors that affect patient safety nursing activity, and its explanatory power was 7.5%(Adj R²=.075, p<.001). For patient safety nursing activity, it is proposed to develop and apply a education program that strengthens practical training for effective coping after safety accidents along with risk prediction training to prevent before safety accidents.

• Journal of Internet of Things and Convergence
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• v.9 no.6
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• pp.63-73
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• 2023

The purpose of this study is to identify the level of learning flow, learning satisfaction, academic self-efficacy, academic achievement, and academic stress of nursing students who experienced non-face-to-face online lectures, and to investigate the correlation between variables and the factors affecting academic stress. The data of this study was collected from 143 students at a nursing college in Seoul, through a Google online questionnaire from September 1, 2023 to September 25, 2023, and descriptive statistics, Student's t-test, analysis of variance, Pearson's Correlation, and linear multiple regression were conducted using SPSS Statistics 25.0. Following an analysis of the difference according to general characteristics, academic stress showed significant difference according to Motivation for applying to department(F=4.465, p=.005) and Major satisfaction(F=36.499, p=.000) of the subjects. The result of analyzing the correlation academic stress was negatively correlated with learning flow (r=-.464, p<.010), academic self-efficacy (r=-.522, p<.010), and academic achievement (r=-.379, p<.010), but learning satisfaction was not correlated with academic stress. Variables affecting academic stress were major satisfaction (𝛽=.367, p<.01), learning flow (𝛽=-.186, p<.05), and academic self-efficacy (𝛽=-.241, p<.05), and the explanatory power for academic stress was 40%. The results of this study can be used as basic data for intervention programs for relieving academic stress of nursing students.

• Tuberculosis and Respiratory Diseases
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• v.41 no.5
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• pp.521-530
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• 1994

Background : The past studies on prediction formulas of pulmonary function parameters in healthy nonsmoking Korean adults have been performed in relatively small number of subjects and the reported results were restricted on a few parameters. Also there was no systematic investigation into the effect of smoking on pulmonary function parameters in smokers who have no respiratory symptoms. Therefore we attempted to establish prediction formulas of pulmonary function parameters and examined the effect of smoking on pulmonary function parameters. Methods We analyzed the result of parameters derived from the forced expiratory spirogram in 1,067 nonsmoking subjects from June in 1990 to December in 1991. They consisted of 306 males and 761 females and had neither respitatory symptoms nor history of respiratory disease. We derived prediction formulas by multiple linear regression method from their age, heights, and weights in each sex. To examine the effect of smoking on pulmonary function parameters, we classified 383 smoking men into three groups according to the past amount of smoking as follows : i.e. group of smokers who have smoked below 10 pack-years, 10-20 pack-years and above 20 pack-years. Regarding each group of past smoking as an independent dummy variable, we analyzed pulmonary function parameters including nonsmoking men as a baseline by multiple linear regression. We evaluated the smoking effect on pulmonary function parameters according to estimated p-value. Result : 1) Prediction formulas for pulmonary function parameters in each sex were derived. 2) The past smoking less than 10 pack-years does not give any effect on pulmonary function parameters. The past smoking of 10~20 pack-years showed significant negative correlation with $FEV_1$/FVC and FEF 25~75%, and the smoking above 20 pack years showed negative correlation with $FEV_1$ and $FEV_1$/FVC. Conclusion : We have got prediction formulas of pulmonary function parameters which is driven from forced expiratory spirogram in nonsmoking Korean adults by multiple linear regression from age, heights and weights of subjects. The past smoking more than 10 pack-years showed negative correlation with some pulmonary function parameters of airflow obstruction.

• Journal of Chest Surgery
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• v.39 no.8 s.265
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• pp.579-587
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• 2006

Background: Preoperative risk analysis for Fontan candidates is still less than optimal in that patients with apparently low risks may have poor surgical outcome; prolonged pleural drainage, protein losing enteropathy, pulmonary thromboembolism and death. We hypothesized that low pulmonary vascular compliance (PVC) is a risk factor for prolonged pleural effusion drainage after the Fontan operation. Material and Method: A retrospective review of 96 consecutive patients who underwent the Extracardiac Fontan procedures (median age: 3.9 years) was performed. Fontan risk score (FRS) was calculated from 12 categorized preoperative anatomic and physiologic variables. PVC $(mm^2/m^2{\cdot}mmHg)$ was defined as pulmonary artery index $(mm^2/m^2)$ divided by total pulmonary resistance $(W.U{\cdot}/m^2)$ and pulmonary blood flow $(L/min/m^2)$ based on the electrical circuit analogue of the pulmonary circulation. Chest tube indwelling time was log-transformed (log indwelling time, LIT) to fit normal distribution, and the relationship between preoperative predictors and LIT was analyzed by multiple linear regression. Result: Preoperative PVC, chest tube indwelling time and LIT ranged from 6 to 94.8 $mm^2/mmHg/m^2$ (median: 24.8), 3 to 268 days (median: 20 days), and 1.1 to 5.6 (mean: 2.9, standard deviation: 0.8), respectively. FRS, PVC, cardiopulmonary bypass time (CPB) and central venous pressure at postoperative 12 hours were correlated with LIT by univariable analyses. By multiple linear regression, PVC (p=0.0018) and CPB (p=0.0024) independently predicted LIT, explaining 21.7% of the variation. The regression equation was LIT=2.74-0.0158 PVC+0.00658 CPB. Conclusion: Low pulmonary vascular compliance is an important risk factor for prolonged pleural effusion drainage after the extracardiac Fontan procedure.

• Journal of the Korean Institute of Landscape Architecture
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• v.42 no.3
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• pp.1-12
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• 2014

Urban Green space takes charge of the important role for the physical activity and promotion of health to the residents. Therefore, this study is trying to examine the relationship between the various characteristics of green space and green space usage for physical activity and health promotion. A questionnaire survey was conducted to obtain the information about patterns of green space usage and perceived neighborhood environments for the residents living in Changwon-si, Gyeongsangnam-do(n=541). Geographic Information System(GIS) was used to construct spatial data about green space accessibility and physical neighborhood environments. A Multiple Linear Regression model was used to examine the association between the characteristics of green space and physical activity, perceived health status and BMI(Body Mass Index). The study results revealed that the residents' physical activities are positively and directly influenced by the number of available public parks and green spaces in the vicinity(${\leq}200m$). The frequency at which residents witness others exercising nearby or the perceived abundance of low-cost gym facilities also factor as positive influences. The closer to the park, the higher the number of parks and area of green spaces, the more comfortable the walk thereto and the denser the neighboring residential area distribution, the perceived health level was found to be the more positively influenced. Further, it was verified that BMI is correlated with the number of public parks and green spaces within 400 m of the resident's home as well as the safety of walkways, the density of neighboring residential areas, the ratio of road, and the density of crosswalk. The significant multiple regression models between the characteristics of green spaces and physical activities and perceived health level were extracted within the significance level of 10%. This study will contribute to provide better understanding the ways in which green space and neighborhood characteristics are associated with physical activity and health. The result of this research will be available in the landscape architecture plan aimed at improving the use of green space for physical activity and reducing obesity.

• Health Policy and Management
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• v.34 no.3
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• pp.261-270
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• 2024

Background: Various researchers are calculating the health adjusted life expectancy (HALE) at the regional level in South Korea using several methods, most studies merely enumerate the differences in healthy life expectancy based on social characteristics. This study aims to analyze the association between various sociodemographic factors and HALE at the regional level. Methods: To calculate HALE, we utilized the various data sources, including National Health Insurance claims data, and applied the Sullivan's method. We conducted multiple linear regression with regional socioeconomic variables from Korean Statistical Information Service. For the multiple linear regression analysis, we designed three regression models. Model 1 comprised solely socioeconomic variables, model 2 involved both socioeconomic variables and individual health behaviors, and model 3 integrated model 2 with healthcare utilization. Results: The analysis shows that an increase in financial independence (p<0.05), population density (p<0.1), and the number of doctors (p<0.05) associated with an increase in HALE, whereas an increase in the number of beds (p<0.01) was associated with a decrease in HALE. In case of the obesity rate, in model 2 (p<0.1) and model 3 (p<0.05), there was a negative association between HALE and obesity rate. Conclusion: Amidst various variables, it was observed that increased financial independence in specific regions had association with an increase in HALE, highlighting the need for stronger local governance in South Korea. Additionally, the inverse association between hospital beds and HALE suggests several implications, such as the appropriate deployment of healthcare resources. To gain a deeper understanding of the relationship between hospital beds and HALE, further analysis distinguishing different types of hospital beds across healthcare institutions seems necessary.

• Journal of Intelligence and Information Systems
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• v.22 no.4
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• pp.19-43
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• 2016

This study examines the causes of the Asian exchange rate crisis and compares it to the European Monetary System crisis. In 1997, emerging countries in Asia experienced financial crises. Previously in 1992, currencies in the European Monetary System had undergone the same experience. This was followed by Mexico in 1994. The objective of this paper lies in the generation of useful insights from these crises. This research presents a comparison of South Korea, United Kingdom and Mexico, and then compares three different models for prediction. Previous studies of economic crisis focused largely on the manual construction of causal models using linear techniques. However, the weakness of such models stems from the prevalence of nonlinear factors in reality. This paper uses a structural equation model to analyze the causes, followed by a neural network model to circumvent the linear model's weaknesses. The models are examined in the context of predicting exchange rates In this paper, data were quarterly ones, and Consumer Price Index, Gross Domestic Product, Interest Rate, Stock Index, Current Account, Foreign Reserves were independent variables for the prediction. However, time periods of each country's data are different. Lisrel is an emerging method and as such requires a fresh approach to financial crisis prediction model design, along with the flexibility to accommodate unexpected change. This paper indicates the neural network model has the greater prediction performance in Korea, Mexico, and United Kingdom. However, in Korea, the multiple regression shows the better performance. In Mexico, the multiple regression is almost indifferent to the Lisrel. Although Lisrel doesn't show the significant performance, the refined model is expected to show the better result. The structural model in this paper should contain the psychological factor and other invisible areas in the future work. The reason of the low hit ratio is that the alternative model in this paper uses only the financial market data. Thus, we cannot consider the other important part. Korea's hit ratio is lower than that of United Kingdom. So, there must be the other construct that affects the financial market. So does Mexico. However, the United Kingdom's financial market is more influenced and explained by the financial factors than Korea and Mexico.

• Korean Journal of Remote Sensing
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• v.36 no.5_3
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• pp.1053-1066
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• 2020

Sulfur dioxide (SO₂) is primarily released through industrial, residential, and transportation activities, and creates secondary air pollutants through chemical reactions in the atmosphere. Long-term exposure to SO₂ can result in a negative effect on the human body causing respiratory or cardiovascular disease, which makes the effective and continuous monitoring of SO₂ crucial. In South Korea, SO₂ monitoring at ground stations has been performed, but this does not provide spatially continuous information of SO₂ concentrations. Thus, this research estimated spatially continuous ground-level SO₂ concentrations at 1 km resolution over South Korea through the synergistic use of satellite data and numerical models. A stacking ensemble approach, fusing multiple machine learning algorithms at two levels (i.e., base and meta), was adopted for ground-level SO₂ estimation using data from January 2015 to April 2019. Random forest and extreme gradient boosting were used as based models and multiple linear regression was adopted for the meta-model. The cross-validation results showed that the meta-model produced the improved performance by 25% compared to the base models, resulting in the correlation coefficient of 0.48 and root-mean-square-error of 0.0032 ppm. In addition, the temporal transferability of the approach was evaluated for one-year data which were not used in the model development. The spatial distribution of ground-level SO₂ concentrations based on the proposed model agreed with the general seasonality of SO₂ and the temporal patterns of emission sources.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.10 no.1
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• pp.160-169
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• 2000

Daily indoor and outdoor nitrogen dioxide ($NO_2$) concentration for 30 days were measured in 28 houses with questionnaire of housing characteristics in Brisbane, Australia. Using mass balance equation and regression analysis, penetration factors and source strength factors were calculated. The penetration factors of 27 houses except one house were between zero and 1, though penetration factor should be between zero and 1 by means of mass balance equation. Relationship between indoor and outdoor concentrations in each 27 house was calculated using regression analysis. According to the obtained linear regression equation, the slope means penetration factor and the intercept means source strength factor. Calculated mean and standard deviation of coefficients of determination ($R^2$) in electric and gas range houses were $0.70{\pm}0.13$ and $0.57{\pm}0.21$, respectively. The source strength factors were more than zero in 27 houses. Mean and standard deviation of slopes in electric and gas range houses were $0.65{\pm}0.18$ and $0.56{\pm}0.12$, respectively. Mean and standard deviation of intercepts in electric and gas range houses were $1.49{\pm}1.25$ and $5.77{\pm}3.55$, respectively. Air exchange rate and source strength were calculated from penetration factor and source strength factor, respectively. Geometric mean and standard deviation of calculated air exchange rates in 27 houses were $1.1/hr{\pm}1.5$. Presence of gas range was the most significant factor contributing to indoor $NO_2$ level in house characteristics (p=0.003). In gas range houses, source strengths ranged from 4.1 to $33.1cm^3/hr{\cdot}m^3$ with a mean $12.7cm^3/hr{\cdot}m^3$ and a standard deviation 9.8. The source strengths of gas range houses were significantly different from those of electric range houses by t-test (p<0.001)